In our experiments, we adopt two different convolutional neural network (CNN) architectures to evaluate the performance of the proposed method. The first CNN is, as also in [1]}, the classical LeNet [2]} which consists of two convolutional layers, each followed by a \(2\times 2\)  max-pooling layer, and two fully connected layers. The second is VGG [3]} with 13 convolutional layers and 3 fully connected layers.
